les territoires étudiés
Les communes des métropoles de Paris, Lyon, Marseille
Les variables utilisées pour l’étude
Thématique Logement
| X1ry_res |
1573 |
85 |
15 |
| X2ry_res |
1573 |
5.6 |
11 |
| Vacant_Home |
1573 |
8.4 |
4.2 |
| Houses |
1573 |
78 |
32 |
| Flats |
1573 |
21 |
32 |
| Nb_Rooms_1ry_res |
1573 |
4.4 |
0.57 |
| House_1ry_res |
1573 |
79 |
29 |
| Flat_1ry_res |
1573 |
20 |
28 |
| X1ry_res_bf_1919 |
1573 |
16 |
15 |
| X1ry_res_19.45 |
1573 |
7.9 |
4.7 |
| X1ry_res_46.70 |
1573 |
16 |
9.6 |
| X1ry_res_71.90 |
1573 |
27 |
8 |
| X1ry_res_91.05 |
1573 |
15 |
7.5 |
| X1ry_res_06.15 |
1573 |
11 |
6 |
| HH_Moving_Time_lt2y |
1573 |
11 |
2.8 |
| HH_Moving_Time_2to4y |
1573 |
18 |
4.4 |
| HH_Moving_Time_5to9y |
1573 |
17 |
2 |
| HH_Moving_Time_10to19y |
1573 |
21 |
2.6 |
| HH_Moving_Time_20to29y |
1573 |
12 |
1.9 |
| HH_Moving_Time_gt30y |
1573 |
21 |
7.3 |
| X1ry_res_Owner |
1573 |
69 |
15 |
| X1ry_res_Tenant |
1573 |
19 |
6.1 |
| X1ry_res_Social |
1573 |
7.6 |
9 |
| X1ry_res_FreeAcc |
1573 |
1.2 |
1.6 |
| X1ry_res_Carpark |
1573 |
73 |
12 |
| X1ry_res_0car |
1573 |
11 |
6.9 |
| X1ry_res_1car |
1573 |
45 |
6.5 |
| X1ry_res_2car |
1573 |
36 |
10 |
| X1ry_res_3.car |
1573 |
7.5 |
3.3 |
| Pop_per_1ry_res |
1573 |
2.2 |
0.28 |
| X1ry_res_gt0car |
1573 |
89 |
6.9 |
| Pop_per_1ry_res_Owner |
1573 |
2.3 |
0.28 |
| Pop_per_1ry_res_Tenant |
1573 |
2 |
0.24 |
| Pop_per_1ry_res_Social |
1565 |
2.2 |
0.41 |
| Pop_per_1ry_res_FreeAcc |
1573 |
1.7 |
0.36 |
| X1ry_res_Occupancy |
1573 |
19 |
25 |
| Owners_Occupancy |
1573 |
16 |
19 |
| Tenant_Occupancy |
1573 |
1.3 |
2.2 |
| Social_Occupancy |
1573 |
0.82 |
2.7 |
| FreeAcc_Occupancy |
1573 |
0.067 |
0.15 |
| Overcrowding_rate |
1573 |
1.9 |
2.3 |
Thématique Emploi
| X1564_Workforce_rate |
1573 |
75 |
4.2 |
| X1524_Workforce_rate |
1573 |
44 |
7.6 |
| X2554_Workforce_rate |
1573 |
92 |
3.8 |
| X5564_Workforce_rate |
1573 |
55 |
7.7 |
| X1564_men_Workforce_rate |
1573 |
78 |
4 |
| X1524_men_Workforce_rate |
1573 |
48 |
9.2 |
| X2554_men_Workforce_rate |
1573 |
95 |
3.2 |
| X5564_men_Workforce_rate |
1573 |
56 |
9.3 |
| X1564_women_Workforce_rate |
1573 |
73 |
4.7 |
| X1524_women_Workforce_rate |
1573 |
39 |
6.5 |
| X2554_women_Workforce_rate |
1573 |
89 |
4.7 |
| X5564_women_Workforce_rate |
1573 |
53 |
7.3 |
| X1564_Employed_rate_amg_WF |
1573 |
88 |
4.6 |
| X1524_Employed_rate_amg_WF |
1573 |
75 |
8.1 |
| X2554_Employed_rate_amg_WF |
1573 |
90 |
4.4 |
| X5564_Employed_rate_amg_WF |
1573 |
90 |
3.7 |
| X1564_men_Employed_rate_amg_WF |
1573 |
89 |
4.4 |
| X1524_men_Employed_rate_amg_WF |
1573 |
75 |
8.9 |
| X2554_men_Employed_rate_amg_WF |
1573 |
91 |
4.1 |
| X5564_men_Employed_rate_amg_WF |
1573 |
91 |
3.8 |
| X1564_women_Employed_rate_amg_WF |
1573 |
88 |
4.8 |
| X1524_women_Employed_rate_amg_WF |
1573 |
74 |
9 |
| X2554_women_Employed_rate_amg_WF |
1573 |
89 |
4.7 |
| X5564_women_Employed_rate_amg_WF |
1573 |
90 |
4.1 |
| X1564_Unemployed_rate_amg_WF |
1573 |
12 |
4.6 |
| X1524_Unemployed_rate_amg_WF |
1573 |
25 |
8.1 |
| X2554_Unemployed_rate_amg_WF |
1573 |
10 |
4.4 |
| X5564_Unemployed_rate_amg_WF |
1573 |
10 |
3.7 |
| X1564_NonWorking_amg_WF |
1573 |
8.7 |
3.2 |
| X1564_Student_amg_WF |
1573 |
8.3 |
2.6 |
| X1564_Retired_amg_WF |
1573 |
7.8 |
3 |
| X1564_OtherInactive_amg_WF |
1573 |
5.1 |
2.5 |
| X1564_men_Unemplyed_amg_WF |
1573 |
18 |
9.2 |
| X1564_women_Unemplyed_amg_WF |
1573 |
11 |
5.8 |
| X1564_Student_amg_NW |
1573 |
25 |
9.1 |
| X1564_Retired_amg_NW |
1573 |
24 |
9.1 |
| X1564_OtherInactive_amg_NW |
1573 |
15 |
4.6 |
| X1564_NonWorking_amg_POP |
1573 |
33 |
7 |
| X1564_Farmers_amg_WF |
1573 |
2.7 |
5.4 |
| X1564_CraftsBusinessShopkeepers_amg_WF |
1573 |
8.5 |
4.7 |
| X1564_HihgQualWorkers_amg_WF |
1573 |
10 |
6 |
| X1564_IntermediateProf_amg_WF |
1573 |
23 |
6.6 |
| X1564_BlueCollar_amg_WF |
1573 |
23 |
10 |
| X1564_WhiteCollar_amg_WF |
1573 |
28 |
6.2 |
| X1564_Farmers_amg_EmpWF |
1573 |
1.6 |
3.4 |
| X1564_CraftsBusinessShopkeepers_amg_EmpWF |
1573 |
6.6 |
3 |
| X1564_HihgQualWorkers_amg_EmpWF |
1573 |
9.9 |
7.7 |
| X1564_IntermediateProf_amg_EmpWF |
1573 |
24 |
5.9 |
| X1564_BlueCollar_amg_EmpWF |
1573 |
24 |
11 |
| X1564_WhiteCollar_amg_EmpWF |
1573 |
28 |
4.6 |
| X15._men_amg_empWF |
1573 |
50 |
1.6 |
| X15._women_amg_empWF |
1573 |
50 |
1.6 |
| X15._Salaried_amg_empWF |
1573 |
86 |
7.6 |
| X15._NonSalaried_amg_empWF |
1573 |
14 |
7.6 |
| X15._FullTime_amg_empWF |
1573 |
83 |
3.5 |
| X15._men_amg_salWF |
1573 |
50 |
2.5 |
| X15._women_amg_salWF |
1573 |
50 |
2.5 |
| X15._men_amg_nonsalWF |
1573 |
64 |
4.1 |
| X15._women_amg_nonsalWF |
1573 |
36 |
4.1 |
| X15._men_amg_FullTimeWF |
1573 |
85 |
8.3 |
| X15._women_amg_FullTimeWF |
1573 |
15 |
8.3 |
| X15._FullTime_amg_salWF |
1573 |
82 |
4.2 |
Thématique Famille
| SinglePerson_HH |
1554 |
33 |
8.6 |
| SingleMan_HH |
1554 |
15 |
3.7 |
| SingleWoman_HH |
1554 |
18 |
5.4 |
| OtherNoFamily_HH |
1554 |
1.5 |
0.68 |
| Family_HH |
1554 |
65 |
8.9 |
| NoChildFamily_HH |
1573 |
45 |
9.2 |
| ChildFamily_HH |
1573 |
41 |
8.8 |
| SingleParent_HH |
1573 |
13 |
4.8 |
| Farmer_HH |
1554 |
1.3 |
2.4 |
| CraftsBusinessShopkeepers_HH |
1554 |
4.9 |
2 |
| HighQualidied_HH |
1554 |
6.8 |
6 |
| Intermediate_HH |
1554 |
15 |
5.5 |
| BlueCollar_HH |
1554 |
16 |
7.6 |
| WhiteCollar_HH |
1554 |
16 |
3.2 |
| Retired_HH |
1554 |
32 |
9.1 |
| Other_HH |
1554 |
4 |
2.7 |
| X15._SinglePerson_HH |
1573 |
38 |
6.9 |
| Pop_SingleMan_HH |
1554 |
6.7 |
2.4 |
| Pop_SingleWoman_HH |
1554 |
8.2 |
3.4 |
| Pop_OtherNoFamily_HH |
1554 |
1.5 |
0.77 |
| Pop_Family_HH |
1554 |
83 |
6.1 |
| Pop_NoChildFamily_HH |
1554 |
32 |
8.4 |
| Pop_ChildFamily_HH |
1554 |
55 |
8.9 |
| Pop_SingleParent_HH |
1554 |
12 |
4.3 |
| Pop_Farmer_HH |
1554 |
1.5 |
2.9 |
| Pop_CraftsBusinessShopkeepers_HH |
1554 |
6.1 |
2.3 |
| Pop_HighQualidied_HH |
1554 |
8.2 |
7.1 |
| Pop_Intermediate_HH |
1554 |
17 |
5.5 |
| Pop_BlueCollar_HH |
1554 |
19 |
9.1 |
| Pop_WhiteCollar_HH |
1554 |
17 |
3.6 |
| Pop_Retired_HH |
1554 |
22 |
8 |
| Pop_Other_HH |
1554 |
3.1 |
2.3 |
| X1524_amg_15.POP |
1573 |
12 |
3.1 |
| X2554_amg_15.POP |
1573 |
45 |
7.3 |
| X5579_amg_15.POP |
1573 |
35 |
6.9 |
| X80._amg_15.POP |
1573 |
7.9 |
3.4 |
| X15._Single_amg_POP |
1573 |
23 |
4.6 |
| X15._Married_amg_POP |
1573 |
46 |
4.6 |
| X15._nonMarried_amg_POP |
1573 |
54 |
4.6 |
| X1524_amg_HH |
1573 |
12 |
3 |
| X2554_amg_HH |
1573 |
46 |
7.2 |
| X5579_amg_HH |
1573 |
35 |
7.1 |
| X80._amg_HH |
1573 |
6.9 |
3 |
| X1524_amg_Single |
1573 |
3.5 |
2.5 |
| X2554_amg_Single |
1573 |
31 |
7.7 |
| X5579_amg_Single |
1573 |
45 |
6.1 |
| X80._amg_Single |
1573 |
19 |
5.3 |
| Family_w_Children_amg_HH |
1573 |
55 |
9.2 |
| Single_Parent_Family_amg_HH |
1573 |
13 |
4.8 |
| Family_wo_Children_amg_HH |
1573 |
45 |
9.2 |
Thématique Revenus
| D1_st_Living |
1546 |
12120 |
2128 |
| Median_st_Living |
1563 |
21210 |
3020 |
| D9_st_Living |
1546 |
34980 |
6435 |
| Interdecile_91_Ratio |
1546 |
2.9 |
0.57 |
| Taxable_HH |
1546 |
48 |
14 |
| Poverty_amg_Owners |
1460 |
7 |
4.4 |
| Poverty_amg_Tenants |
1498 |
26 |
10 |
| X.30_Poverty |
758 |
21 |
9.6 |
| X3039_Poverty |
1255 |
16 |
9.3 |
| X4049_Poverty |
1380 |
15 |
8.8 |
| X5059_Poverty |
1309 |
14 |
7.4 |
| X6074_Poverty |
1203 |
9.8 |
5.2 |
| X75._Poverty |
879 |
11 |
5.5 |
| Poverty |
1526 |
13 |
6.9 |
| Activity_Income |
1546 |
71 |
14 |
| Salary_Income |
1546 |
62 |
16 |
| Unemployment_Benef |
1546 |
2.8 |
0.7 |
| Self.Employment |
1546 |
5.7 |
2.6 |
| Pensions_Annuities |
1546 |
30 |
10 |
| Estate |
1546 |
9.4 |
2.7 |
| Social_Benef |
1546 |
5.1 |
2 |
| Family_Benef |
1546 |
2.1 |
0.7 |
| Social_Minima |
1546 |
1.9 |
1.2 |
| Housing_Benef |
1546 |
1.1 |
0.6 |
| Tax |
1546 |
-16 |
3.3 |
Thématique Activité
| Wk_Res_Municipality |
1573 |
27 |
17 |
| Wk_Res_County.Municipality |
1573 |
54 |
25 |
| Wk_Res_Region.County |
1573 |
4.8 |
13 |
| Wk_Res_Country.Region |
1573 |
1.7 |
2 |
| Wk_Dom_Com_Abroad |
1573 |
0.18 |
0.23 |
| noTransport_toWk |
1573 |
4.7 |
3 |
| Walk_toWk |
1573 |
5 |
3.3 |
| Bike_toWk |
1573 |
1 |
1 |
| Motorbike_toWk |
1573 |
1.1 |
0.73 |
| Drive_toWk |
1573 |
83 |
8.9 |
| PublicTrans_toWk |
1573 |
3.1 |
6.1 |
| X15._Men_amg_salWF |
1573 |
50 |
2.5 |
| X15._Women_amg_salWF |
1573 |
50 |
2.5 |
| X15._PermanentContract_amg_salWF |
315 |
83 |
5.8 |
| X15._ShortTermContract_amg_salWF |
315 |
11 |
5.4 |
| X15._InterimContract_amg_salWF |
315 |
1.1 |
1.5 |
| X15._SubsidizedWork_amg_salWF |
315 |
1.2 |
1.5 |
| X15._ApprenticeContract_amg_salWF |
315 |
2.3 |
1.6 |
| X15._SelfEmployed_amg_nonsalWF |
315 |
64 |
11 |
| X15._Employers_amg_nonsalWF |
315 |
35 |
11 |
| X15._caregivers_amg_nonsalWF |
315 |
0.89 |
2 |
Thématique Population
| X0014_amg_POP |
1573 |
18 |
3.7 |
| X1529_amg_POP |
1573 |
18 |
3.7 |
| X3044_amg_POP |
1573 |
18 |
3.2 |
| X4559_amg_POP |
1573 |
21 |
1.7 |
| X6074_amg_POP |
1573 |
18 |
4.8 |
| X7589_amg_POP |
1573 |
8.7 |
3.6 |
| X90._amg_POP |
1573 |
1.3 |
0.77 |
| Men |
1573 |
49 |
1.3 |
| X0019_amg_POP |
1573 |
23 |
4.3 |
| X2064_amg_POP |
1573 |
55 |
3.9 |
| X65._amg_POP |
1573 |
21 |
7.8 |
| X15._Farmers_amg_POP |
1573 |
0.95 |
1.9 |
| X15._CraftsBusinessShopkeeper_amg_POP |
1573 |
3.8 |
1.5 |
| X15._ManagersHigherIntellectProf_amg_POP |
1573 |
5.6 |
5 |
| X15._IntermediateProf_amg_POP |
1573 |
13 |
4.8 |
| X15._WhiteCollar_amg_POP |
1573 |
16 |
2.7 |
| X15._BlueCollar_amg_POP |
1573 |
13 |
5.8 |
| X15._Retired_amg_POP |
1573 |
30 |
9.5 |
| X15._OtherNoActivity_amg_POP |
1573 |
14 |
4.4 |
| X0014_men_amg_mPOP |
1573 |
18 |
3.8 |
| X1529_men_amg_mPOP |
1573 |
15 |
3.6 |
| X3044_men_amg_mPOP |
1573 |
18 |
3 |
| X4559_men_amg_mPOP |
1573 |
21 |
1.9 |
| X6074_men_amg_mPOP |
1573 |
18 |
5.2 |
| X7589_men_amg_mPOP |
1573 |
7.3 |
3.2 |
| X90._men_amg_mPOP |
1573 |
0.73 |
0.47 |
| X0019_men_amg_mPOP |
1573 |
25 |
4.6 |
| X2064_men_amg_mPOP |
1573 |
55 |
3.5 |
| X65._men_amg_mPOP |
1573 |
19 |
7.2 |
| X15._men_Farmers_amg_mPOP |
1573 |
1.5 |
2.9 |
| X15._men_CraftsBusinessShopkeeper_amg_mPOP |
1573 |
5.6 |
2.2 |
| X15._men_ManagersHigherIntellectProf_amg_mPOP |
1573 |
6.8 |
6.5 |
| X15._men_IntermediateProf_amg_mPOP |
1573 |
13 |
4.6 |
| X15._men_WhiteCollar_amg_mPOP |
1573 |
7.2 |
3.1 |
| X15._men_BlueCollar_amg_mPOP |
1573 |
22 |
8.5 |
| X15._men_Retired_amg_mPOP |
1573 |
29 |
8.9 |
| X15._men_OtherNoActivity_amg_POP |
1573 |
11 |
3.7 |
| X0014_women_amg_wPOP |
1573 |
17 |
3.8 |
| X1529_women_amg_wPOP |
1573 |
14 |
3.5 |
| X3044_women_amg_wPOP |
1573 |
18 |
3.5 |
| X4559_women_amg_wPOP |
1573 |
20 |
1.7 |
| X6074_women_amg_wPOP |
1573 |
18 |
4.6 |
| X7589_women_amg_wPOP |
1573 |
9.9 |
4.1 |
| X90._women_amg_wPOP |
1573 |
1.9 |
1.1 |
| X0019_women_amg_wPOP |
1573 |
22 |
4.4 |
| X2064_women_amg_wPOP |
1573 |
54 |
4.5 |
| X65._women_amg_wPOP |
1573 |
23 |
8.3 |
| X15._women_Farmers_amg_wPOP |
1573 |
0.44 |
0.97 |
| X15._women_CraftsBusinessShopkeeper_amg_wPOP |
1573 |
2.1 |
1 |
| X15._women_ManagersHigherIntellectProf_amh_wPOP |
1573 |
4.5 |
3.7 |
| X15._women_IntermediateProf_amg_wPOP |
1573 |
14 |
5.2 |
| X15._women_WhiteCollar_amg_wPOP |
1573 |
24 |
4.1 |
| X15._women_BlueCollar_amg_wPOP |
1573 |
4.8 |
3.2 |
| X15._women_Retired_amg_wPOP |
1573 |
30 |
10 |
| X15._women_OtherNoActivity_amg_wPOP |
1573 |
16 |
5.2 |
Thématique Immigration
| French_nlty |
1239 |
96 |
5.3 |
| Stranger |
1239 |
4 |
5.3 |
| Immigrant |
1554 |
5.4 |
6.1 |
| French_nlty_amg_Men |
1239 |
96 |
5.5 |
| Stranger_amg_Men |
1239 |
4.1 |
5.5 |
| Immigrant_amg_Men |
1554 |
5.4 |
6.2 |
| French_nlty_amg_Women |
1239 |
96 |
5.1 |
| Stranger_amg_Women |
1239 |
3.8 |
5.1 |
| Immigrant_amg_Women |
1554 |
5.5 |
6.2 |
| Res_Abroad_2017 |
1239 |
0.25 |
0.26 |
Thématique Géographie
| densite |
1897 |
58 |
105 |
| latitude |
1231 |
6652162 |
408167 |
| longitude |
1231 |
676107 |
330745 |
| SO.NE |
1231 |
1 |
0.46 |
| NO.SE |
1231 |
-0.021 |
0.46 |
Manhattan
Pour construire les graphiques suivants, chaque variable a été dichotomisée par rapport à la médiane (1 pour supérieur à la médiane et 0 pour inférieur à la médiane).
Pour chaque semaine de l’année 2021, les 25 % des territoires les moins vaccinés sont étiquetés 1 et les autres 0.
On calcule l’odds ratio pour chaque variable. Cela permet de repérer les variables qui agissent le plus sur le taux de vaccination.
Dans ls graphique suivants, chaque variable a une position fixe sur l’axe des abscisses.
L’axe des ordonnées représente le maximum entre l’odds ratio et son inverse. Ainsi une variable qui agit fortement sur le taux de vaccination aura une position élevée sur le graphque indépendamment de l’influence positive ou négative de son influence. Les variables sont classées par thématique.
La grosseur de chaque point est proportionnelle à \(-\log_{10}(p)\).
Puis pour connaitre l’influebce de chaque variable, on ne trace uniquement l’odds ratio et enfin son inverse.
Données à la semaine non cumulées
Par classe d’âge : données cumulées
Données données cumulées restreintes de la semaine 22 à 27
Données données cumulées restreintes de la semaine 28 à 34
Couverture vaccinale par tranche d’âge
| 2021-22 |
1.78 |
27.17 |
44.88 |
64.26 |
75.74 |
77.11 |
| 2021-27 |
9.66 |
44.16 |
59.58 |
72.13 |
80.58 |
79.81 |
| 2021-34 |
25.22 |
70.03 |
78.8 |
83.83 |
86.89 |
83.79 |